Sampling transactions from multi-level log file records

ABSTRACT

A log file contains operation records, each operation record is of a certain type, and each operation record is associated with a transaction. A plurality of operation records is read from the log file into a record store. Records of the plurality of operation records of each operation record type are sampled at a predefined sampling rate. Operation records in the plurality of operations records are identified that are associated with completed transactions of which the sampled operation records are associated. The identified operation records are then extracted from the record store into a data store.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/733,452, filed Jan. 3, 2013, which is hereby incorporated byreference in its entirety.

FIELD OF THE INVENTION

The present invention relates generally to the field of sampling of datarecords, and more particularly to sampling of sub-record types ofmulti-level records followed by retrieval of the full multi-levelrecord.

BACKGROUND OF THE INVENTION

Sampling of database transactions from a database transactions log filecan provide useful information about the database performance andenvironment. If the transactions are single-level transactions, that is,each transaction is only a single database operation, for example, oneSQL statement, then the sampling of transactions from the log file israther straight forward. Typically, database transactions aremulti-level transactions. Each transaction can include several databaseoperations. In addition, while the database operation records for atransaction will usually appear in the proper order in the databasetransaction log file, the database operation records from multipletransactions can be intermixed. With multi-level transactions, to samplea database transaction from the log file requires identifying andextracting all the database operation records associated with thetransaction. These factors can complicate sampling of transactions froma database transaction log file.

SUMMARY

Embodiments of the present invention disclose a method, computer programproduct, and system for sampling transactions from multi-level log filerecords. A log file contains operation records, each operation record isof a certain type, and each operation record is associated with atransaction. A plurality of operation records is read from the log fileinto a record store. Records of the plurality of operation records ofeach operation record type are sampled at a predefined sampling rate.Operation records in the plurality of operations records are identifiedthat are associated with completed transactions of which the sampledoperation records are associated. The identified operation records arethen extracted from the record store into a data store.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a functional block diagram of a transaction sampling system inaccordance with an embodiment of the present invention.

FIG. 2 is a functional block diagram of a transaction sampling module ofthe transaction sampling system illustrated in FIG. 1, in accordancewith first embodiments of the present invention.

FIGS. 3A, 3B, and 3C are a flowchart depicting operational steps of thetransaction sampling module of the transaction sampling systemillustrated in FIG. 1, in accordance with first embodiments of thepresent invention.

FIG. 4 is a functional block diagram of a transaction sampling module ofthe transaction sampling system illustrated in FIG. 1, in accordancewith second embodiments of the present invention.

FIGS. 5A, 5B, and 5C are a flowchart depicting operational steps of thetransaction sampling module of the transaction sampling systemillustrated in FIG. 1, in accordance with second embodiments of thepresent invention.

FIG. 6 is a block diagram of components of the computing device of thetransaction sampling system of FIG. 1, in accordance with an embodimentof the present invention.

DETAILED DESCRIPTION

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer-readablemedium(s) having computer readable program code/instructions embodiedthereon.

Any combination of computer-readable media may be utilized.Computer-readable media may be a computer-readable signal medium or acomputer-readable storage medium. A computer-readable storage medium maybe, for example, but not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus, ordevice, or any suitable combination of the foregoing. More specificexamples (a non-exhaustive list) of a computer-readable storage mediumwould include the following: an electrical connection having one or morewires, a portable computer diskette, a hard disk, a random access memory(RAM), a read-only memory (ROM), an erasable programmable read-onlymemory (EPROM or Flash memory), an optical fiber, a portable compactdisc read-only memory (CD-ROM), an optical storage device, a magneticstorage device, or any suitable combination of the foregoing. In thecontext of this document, a computer-readable storage medium may be anytangible medium that can contain, or store a program for use by or inconnection with an instruction execution system, apparatus, or device.

A computer-readable signal medium may include a propagated data signalwith computer-readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer-readable signal medium may be any computer-readable medium thatis not a computer-readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer-readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on a user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computer,or entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in acomputer-readable medium that can direct a computer, other programmabledata processing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer-readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce acomputer-implemented process such that the instructions which execute onthe computer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

Embodiments of the invention operate generally to sample databaseoperation records of multi-level transactions in a transaction log fileto provide at least a minimum representative sample of each type ofdatabase operation record. However, since analysis is typicallyperformed at the transaction level, the complete transaction to whichthe sampled database operation record belongs is extracted from the logfile. In first embodiments of the invention, the log file is dividedinto sample sets, for example, a certain percentage of the log filerecord count, or a fixed number of log file records, and each sample setis processed in turn. As a sample set is read from the log file, thedatabase operation records are split out based on the type of databaseoperation. When a sample set has been read, each database operation typeis sampled. For example, a fixed number of samples are randomly selectedfor each database operation type. After all database operation typeshave been sampled, and the complete transactions of each sampleddatabase operation record have been extracted, the next sample set isprocessed.

In second embodiments of the invention, sampling occurs as thetransaction log file is read. An sample proportion or sample proportionsby operation type are defined, for example 15% for all operation types.Each separate database operation type is regularly sampled at a rateapproximately equal to its associated sample proportion. For eachdatabase operation type record sampled, the complete transactionassociated with the sampled record is extracted for follow-on analysis.

The present invention will now be described in detail with reference tothe figures. FIG. 1 is a functional block diagram illustrating atransaction sampling system 100 in accordance with an embodiment of thepresent invention. Transaction sampling system 100 includes computingdevice 110, which further includes transaction processing system 120,database management system 130, and transaction analysis system 140.

In preferred embodiments of the invention, computing device 110 can be,for example, a mainframe or mini computer, a laptop, a netbook personalcomputer (PC), or a desktop computer. Transaction sampling system 100 isshown as being wholly implemented on computing device 110. However,transaction sampling system 100 may operate in a distributed environmentin which one or more of its components are implemented across aplurality of computing devices that communicate over a network, such asa local area network (LAN) or a wide area network (WAN) such as theInternet. For example, transaction analysis system 140 may operate on aseparate computing device having sufficient capabilities to support onlythe operation of the transaction analysis system. In general,transaction sampling system 100 can execute on any computing device 110,or combination of computing devices, satisfying desired implementationrequirements, and as described in relation to FIG. 6.

Transaction processing system 120 includes transaction manager 122, logmanager 124, and transaction log file 126. Transaction manager 122manages the processes that execute transactions against database 132 viadatabase management system 130. Transaction manager 122 also manages alltransactions so as to maintain data consistency in database 132. This isaccomplished through the use of log manager 124. Log manager 124, amongits other activities, records each transaction operation of atransaction workload, such as the execution of SQL statements in atransaction, in a database operation record to transaction log file 126.

Database management system 130 includes database 132, which may reside,for example, on tangible storage device 608 (see FIG. 6). Databasemanagement system 130 manages access to database 132, and manages theresources associated with database 132, such as disk space.

Transaction analysis system 140 operates generally to analyze executionsof a transaction workload, and provide, for example, systems andapplications programmers and systems administrators information todetermine, for example, the most efficient organization of a database132, or of a transaction workload, or for determining the most efficientdatabase management system 130 or transaction processing system 120. Theinformation that transaction analysis system 140 processes is derivedfrom transaction log file 126. For example, the transaction log file 126information pertaining to executions of a transaction workload arestored on disk, such as tangible storage device 608, after eachtransaction workload completes, and this information is made availableto transaction analysis system 140 for analysis.

Transaction analysis system 140 includes transaction sampling module142, which is the focus of the present invention. Transaction samplingmodule 142, the operation of which is described in more detail below,operates generally to sample database operation records from transactionlog file 126 at the database operation type, and then to identify andextract all database operation records for the transactions of thesampled records so as to have complete multi-level transactions. Thesemulti-level transactions may then be analyzed by transaction analysissystem 140 to provide, for example, the performance informationdescribed above.

Embodiments of the invention are described with respect to thecomponents and their functionality as presented in FIG. 1. Otherembodiments of the invention may perform the invention as claimed withdifferent functional boundaries between components. For example, thefunctionality of transaction sampling module 142 may be implemented as astandalone component, or as a function of transaction processing system120.

In embodiments of the invention, various constraints and assumptionsapply. One constraint is that only complete multi-level transactions areextracted by transaction sampling module 142 from transaction log file126. Thus, if a database operation record is sampled, all other databaseoperation records belonging to the same multi-level transaction shouldbe extracted from transaction log file 126. If the full transactioncannot be extracted, then the transaction should be rejected as far astransaction sampling is concerned.

One operating assumption is that all database operation records for atransaction will appear in transaction log file 126 in the order ofexecution within the transaction. Thus, if an end-of-transactiondatabase operation record appears in transaction log file 126, then noother database operation record for this transaction will appear in thetransaction log file following the end-of-transaction record.

Another operating assumption is that all database operation records fora transaction will be found within a certain defined transaction span.As mentioned above, the database operation records in transaction logfile 126 from the multi-level transactions of a workload can beintermixed. In other words, the database operation records of asubsequent multi-level transaction can appear in transaction log file126 before the end-of-transaction database operation record of aprevious multi-level transaction. Thus, the transaction span should belarger than the number of transactions found in the multi-leveltransaction of the transaction workload having the largest number ofdatabase operations. The transaction span is typically based on an inputto the algorithm, for example 500 records, and can be based on actualstatistics related to the transaction span for various transactionworkloads. The transaction span can be adjusted, for example, toaccommodate performance and accuracy considerations.

FIG. 2 is a functional block diagram of transaction sampling module 142of transaction sampling system 100 illustrated in FIG. 1, in accordancewith a first embodiment of the present invention. In a first embodiment,transaction sampling module 142, the operation of which is explained inmore detail below, includes sampling logic module 200, transaction logfile read buffer 202, database operation types sampling buffers 204,transactions-to-operations table 206, committed transactions table 208,and sampled transactions table 210. Sampling logic module 200 containsprogramming code, firmware logic, hardware, or a combination of these,to control the operations associated with performing the databaseoperations record sampling and transaction extraction.

Transaction log file read buffer 202 stores the database operationrecords in a sample set of the transaction workload read from log file126. In a first embodiment, the size of transaction log file read buffer202 is at least the number of records in a sample set plus twice thetransaction span. Transaction log file read buffer 202 will include therecords from the sample set, plus a transaction span of records bothbefore and after the sample set. The transaction spans before and afterthe sample set will help to ensure that complete transactions fordatabase operation records sampled at or near the beginning or end ofthe sample set will be available in transaction log file read buffer 202for extraction.

Database operation types sampling buffers 204 is a set of buffers thatincludes one buffer for each type of database operation record that isdesired to be sampled in the transaction workload. The size of eachbuffer should be enough to store the largest number of records of thespecific type likely to be included in a sample set. In someembodiments, database operations records are written to locations indatabase operation types sampling buffers 204. In other embodiments,pointers to database operations records in transaction log file readbuffer 202 are written to locations in database operation types samplingbuffers 204, for example, buffer addresses or record references.

Transactions-to-operations table 206 will include an entry for eachdifferent transaction included in a sample set and the pre- andpost-sample set transaction span on either side of the sample set, andwill include sub-entries associated with each transaction entry for eachdatabase operation record belonging to the transaction. Committedtransactions table 208 will include an entry for each transaction towhich an end-of-transaction database operation record in a sample setplus pre- and post-sample set transaction span belongs. Sampledtransactions table 210 will include an entry for each transaction thatis extracted from transaction log file read buffer 202.

FIGS. 3A, 3B, and 3C are a flowchart depicting operational steps oftransaction sampling module 142 of transaction sampling system 100illustrated in FIG. 1, in accordance with first embodiments of thepresent invention. When a second or subsequent sample set is read fromtransaction log file 126 into transaction log file read buffer 202, theoperation begins by processing the transaction span of records justprior to the sample set. These records will be in transaction log fileread buffer 202 after processing the previous sample set, and thetransaction log file read buffer address pointer will be set to thebeginning record of the pre-sample set transaction span (see step 330).The pre-sample set transaction span records are read, andtransactions-to-operations table 206 is updated for each record (step300).

After transactions-to-operations table 206 is updated for eachpre-sample set transaction span record (step 300), database operationrecords from the sample set are read one at a time (step 302). Becausethe post-sample set transaction span from the previous sample setprocessing is part of the current sample set, these database operationrecords can be read from the transaction log file read buffer 202. Afterthe records in the post-sample set transaction span from the previoussample set have been read from transaction log file read buffer 202, theremaining records in the sample set, and the post-sample set transactionspan for the current sample set processing, are read from transactionlog file 126.

If all database operation records in the current sample set have notbeen read (decision step 304, “N” branch), the just-read record is, forexample, copied into the appropriate database operation type samplingbuffer 204 (step 306). The transactions-to-operations table 206 is thenupdated for the just-read record (step 308). If all database operationrecords in the current sample set have been read (decision step 304, “Y”branch), copying the just-read record into a database operation typesampling buffer 204 is skipped. In certain embodiments, counters can bedefined to track record counts by type to determine actual counts andproportions by record type. Such information can be used, for example,in determining sampling proportions by record type.

If the database operation record is an end-of-transaction record(decision step 310, “Y” branch), an entry for the transaction is addedto the committed transactions record table 208 (step 312). If thedatabase operation record is not an end-of-transaction record (decisionstep 310, “N” branch), the committed transactions record table 208 isnot updated.

If all database operation records for the current sample and allpost-sample set transaction span records set have not been read in(decision step 314, “N” branch), the next database operation record isread from transaction log file read buffer 202 (step 302). If alldatabase operation records for the current sample set and allpost-sample set transaction span records have been read in (decisionstep 314, “Y” branch), sampling of database operation records fromdatabase operation types sampling buffers 204 begins (step 316).

In a first embodiment, sampling occurs for each type of databaseoperation record by performing a random sampling of each of the databaseoperation types sampling buffers 204. For example, as mentioned above, acertain number of samples can be selected from each of the samplingbuffers to ensure that each database operation type record is sampled.In other embodiments, different sampling schemes may be used. Forexample, each database operation type can have a different samplingproportion. Because transaction analysis is typically performed at thetransaction level, for each sampled database operation record sampled,the entire transaction is extracted for further analysis.

After a database operation record has been sampled from a databaseoperation types sampling buffer 204 (step 316), sampling logic module200 determines if the transaction to which the sampled databaseoperation record belongs has already been extracted as a result of aprevious database operation record sampling (decision step 318). If thetransaction to which the sampled database operation record belongs hasalready been extracted (decision step 318, “Y” branch), no furtherprocessing for the sampled database operation record is done, and thenext database operation record sampling is performed (step 316).

If the transaction to which the sampled database operation recordbelongs has not already been extracted (decision step 318, “N” branch),sampling logic module 200 determines if the transaction to which thesampled database operation record belongs has been committed, i.e., if acopy of the end-of-transaction record is in transaction log file readbuffer 202 (decision step 320). If the transaction to which the sampleddatabase operation record belongs has not been committed (decision step320, “N” branch), no further processing for the sampled databaseoperation record is done, and the next database operation recordsampling is performed (step 316). If the transaction to which thesampled database operation record belongs has been committed (decisionstep 320, “Y” branch), sampling logic module 200 extracts all databaseoperation records for the transaction, based on the corresponding entryin transactions-to-operations table 206, and adds an entry to sampledtransactions table 210 (step 322).

If all sampling of the current sample set of database operations recordsfrom the database operation types sampling buffers 204 has not beencompleted (decision step 324, “N” branch), the next database operationrecord is sampled from the database operation types sampling buffers 204(step 316). If all sampling of the current sample set has been completed(decision step 324, “Y” branch), sampling logic module 200 determines ifall sample sets have been processed (decision step 326). If all samplesets of the transaction workload have been processed (decision step 326,“Y” branch), processing ends. If all sample sets have not been processed(decision step 326, “N” branch), setup for processing of the next sampleset is performed. Transaction-to-operations table 206, committedtransactions table 208, and database operation types sampling buffers204 are cleared (step 328). The read pointer for transaction log fileread buffer 202 is also set back to the address of the first record ofthe pre-sample set transaction span (step 330). Then processing of thepre-sample set transaction span records for the next sample set isperformed (step 300).

FIG. 4 is a functional block diagram of transaction sampling module 142of transaction sampling system 100 illustrated in FIG. 1, in accordancewith second embodiments of the present invention. In a secondembodiment, transaction sampling module 142, the operation of which isexplained in more detail below, includes sampling logic module 400,transaction log file read buffer 402, database operation types samplingcounters 404, transactions-to-operations table 406, committedtransactions table 408, pending sampled transactions table 410, sampledtransactions table 412, and read transactions buffer 414. Sampling logicmodule 400 contains programming code, firmware logic, hardware, or acombination of these, to control the operations associated withperforming the database operations record sampling and transactionextraction.

Transaction log file read buffer 402 stores the database operationrecords as they are read from log file 126. In a first exemplaryembodiment, log file read buffer 402 is implemented as a circular bufferhaving a length equal to the transaction span. The length being equal tothe transaction span attempts to ensure that if a sampled databaseoperations record is the last record of a transaction, the previousrecords of transaction are available for extraction, and if the sampleddatabase operations record is the first record of a transaction, atleast a transaction span of records following the first record of thetransaction will be read and searched for records belonging to thetransaction.

Database operation types sampling counters 404 are a set of counters,one for each type of database operation record in the transactionsassociated with the transaction workload, and are incremented as eachassociated type of database operation record is read from log file 126.In a preferred embodiment, each type of database operation record issampled at a regular rate equal to the next lower integer of thereciprocal of the target sample proportion. For example, if the desiredsample proportion is defined as 15% of the transaction log file size,the next lower integer of the reciprocal of 0.15 is 6. Thus, each 6threcord for each database operation record type is sampled. This might beimplemented, for example, using a modulus function of a samplingcounter. In certain embodiments, each type of database operation recordcan have a different target sample proportion, and thus a differentsampling rate.

Transactions-to-operations table 406 will include an entry for eachdifferent transaction read from log file 126, and will includesub-entries associated with each transaction entry for each databaseoperation record read from log file 126 belonging to the transaction.Committed transactions table 408 will include an entry for eachend-of-transaction database operation record read from log file 126.Pending sampled transactions table 410 will contain an entry for eachtransaction associated with a sampled database operations record forwhich an end-of-transaction database operation record has not yet beenread from log file 126. Sampled transactions table 412 will include anentry for each complete transaction that is extracted from transactionlog file read buffer 402.

Read transaction buffer 414 will include one entry per transaction readfrom log file 126, written to the buffer when the first databaseoperation record of a transaction is read. In a preferred exemplaryembodiment, read transaction buffer 414 is implemented as a circularbuffer with length equal to the transaction span. The purpose of readtransaction buffer 414 is to indicate transaction and associateddatabase operation record entries that can be cleared from othertransaction entry tables and buffers in transaction sampling module 142.As each database operation record of a transaction is read from log file126, the address pointer of read transaction buffer 414 is advanced byone buffer entry. When the address pointer encounters a buffer entrycontaining a transaction identifier, this indicates that the addresspointer has come full circle in the buffer back to the transactionidentifier entry, and that a transaction span of log file records hasbeen processed between writing the transaction identifier to the bufferentry and the address pointer returning to the transaction identifierentry. Because a transaction span of log file records has beenprocessed, it is assumed that all database operation records in thetransaction have been read from log file 126. If any of the databaseoperation records in the transaction were flagged for sampling, it isassumed that the complete transaction has been extracted fromtransaction log file read buffer 402, and table and buffer entriesassociated with the transaction may now be cleared.

In certain implementations, pending sampled transactions table 410 isimplemented as a circular buffer with a length equal to the transactionspan, similar to the preferred implementation of read transaction buffer414. In such implementations, similar to the way that read transactionbuffer 414 is used, the pending sampled transactions buffer can be usedto identify transactions to be cleared from the tables and buffers oftransaction sampling module 142 if an end-of-transaction record for atransaction identified in the pending sampled transactions buffer is notread within a transaction span of log file records of an associatedfirst database operation record flagged to be sampled.

FIGS. 5A, 5B, and 5C are a flowchart depicting operational steps oftransaction sampling module 142 of transaction sampling system 100illustrated in FIG. 1, in accordance with second embodiments of thepresent invention. In these embodiments, the operation of transactionsampling module 142 is generally divided between two functions. Thefirst function is directed to reading database operation records fromlog file 126, associating the database operations records to thetransactions to which they belong, indicating when complete transactionsare available for extracting, and cleaning up the tables and buffers toremove transaction related entries for transactions that have passed outof the active transaction span. The second function is directed tosampling of database operation records and extracting completetransactions associated to the sampled records. As described below, theoperational steps associated with these two functions are interleaved toa certain degree.

As each database operation record is read from log file 126 intotransaction log file read buffer 402 (step 500), the database operationtype sampling counter 404 associated with the database operation recordtype is incremented, and an entry is added or updated intransactions-to-operations table 406 (step 502).

When the database operation record is read from log file 126, theaddress pointer for read transaction buffer 414 is advanced to the nextentry, and sampling logic module 400 determines if the entry is empty(decision step 504). If the buffer entry is not empty (decision step504, “N” branch), the buffer entry is cleared, and transaction anddatabase operation record entries associated with the transactionidentifier in the read transaction buffer 414 entry are also clearedfrom transactions-to-operations table 406, committed transactions table408, and pending sampled transactions table 410 (step 506).

Sampling logic module 400 then determines if the database operationrecord read from log file 126 is the first record read of the associatedtransaction that has been read (decision step 508). This is accomplishedby determining if an entry for the transaction identifier of thedatabase operation record is in read transactions buffer 414. If thedatabase operation record read from log file 126 is the first recordread of the associated transaction, as determined by finding no entryfor the transaction identifier of the database operation record in readtransactions buffer 414 (decision step 508, “Y” branch), then an entryis written to the read transactions buffer (step 510).

Sampling logic module 400 then determines if the database operationrecord read from log file 126 is an end-of-transaction record (decisionstep 512). If the database operation record read from log file 126 is anend-of-transaction record (decision step 512, “Y” branch), committedtransactions table 408 is updated with the transaction identifier towhich the log file 126 record belongs (step 514).

If the transaction identifier associated with the newly readend-of-transaction record is included in pending sampled transactionstable 412 (decision step 516, “Y” branch), indicating that an earlierrecord associated with the transaction was flagged to be sampled but alldatabase operation records of the transaction had not yet been read fromlog file 126, then all database operation records for the transactionare extracted (step 518). Entries in transactions-to-operations table406 are used to identify and locate all records for a transaction intransaction log file read buffer 402. An entry for the extractedtransaction is included in sampled transactions table 412, and thecorresponding entry in pending sampled transactions table 410 is cleared(step 520).

Sampling logic module 400 then determines if the database operationrecord read from log file 126 is to be sampled (decision step 522), asdescribed above in relation to FIG. 4 and database operation typessampling counters 404. If the database operation record is not to besampled (decision step 522, “N” branch), then sampling logic module 400determines if all database operation records have been read from logfile 126 (decision step 532). If all log file records have been read(decision step 532, “Y” branch), then processing ends. If all log filerecords have not been read (decision step 532, “N” branch), then thenext database operation record is read from log file 126 (step 500).

If the database operation record is to be sampled (decision step 522,“Y” branch), then sampling logic module 400 determines if thetransaction associated with the database operation record to be sampledhas an entry in committed transactions table 408 (decision step 524). Ifthe transaction associated with the database operation record to besampled does not have an entry in committed transactions table 408(decision step 524, “N” branch), an entry is added or updated in pendingsampled transactions table 410 (step 526), and the next databaseoperation record is read from log file 126 (step 500).

If the transaction associated with the database operation record to besampled does have an entry in committed transactions table 408 (decisionstep 524, “Y” branch), then all database operation records for thetransaction are extracted from transaction log file read buffer 402(step 528), and an entry for the extracted transaction is included insampled transactions table 412 (step 530). If all log file records havebeen read (decision step 532, “Y” branch), then processing ends. If alllog file records have not been read (decision step 532, “N” branch),then the next database operation record is read from log file 126 (step500).

FIG. 6 depicts a block diagram of components of computing device 110 oftransaction sampling system 100 of FIG. 1, in accordance with anembodiment of the present invention. It should be appreciated that FIG.6 provides only an illustration of one implementation and does not implyany limitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironment may be made within the scope and spirit of the invention.

Computing device 110 can include one or more processors 602, one or morecomputer-readable RAMs 604, one or more computer-readable ROMs 606, oneor more tangible storage devices 608, device drivers 612, read/writedrive or interface 614, and network adapter or interface 616, allinterconnected over a communications fabric 618. Communications fabric618 can be implemented with any architecture designed for passing dataand/or control information between processors (such as microprocessors,communications and network processors, etc.), system memory, peripheraldevices, and any other hardware components within a system.

One or more operating systems 610, and transaction processing system120, database management system 130, and transaction analysis system 140are stored on one or more of the computer-readable tangible storagedevices 608 for execution by one or more of the processors 602 via oneor more of the respective RAMs 604 (which typically include cachememory). In the illustrated embodiment, each of the computer-readabletangible storage devices 608 can be a magnetic disk storage device of aninternal hard drive, CD-ROM, DVD, memory stick, magnetic tape, magneticdisk, optical disk, a semiconductor storage device such as RAM, ROM,EPROM, flash memory or any other computer-readable tangible storagedevice that can store a computer program and digital information.

Computing device 110 can also include a R/W drive or interface 614 toread from and write to one or more portable computer-readable tangiblestorage devices 626. Transaction processing system 120, databasemanagement system 130, and transaction analysis system 140 on computingdevice 110 can be stored on one or more of the portablecomputer-readable tangible storage devices 626, read via the respectiveR/W drive or interface 614 and loaded into the respectivecomputer-readable tangible storage device 608.

Computing device 110 can also include a network adapter or interface616, such as a TCP/IP adapter card or wireless communication adapter(such as a 4G wireless communication adapter using OFDMA technology).Transaction processing system 120, database management system 130, andtransaction analysis system 140 on computing device 110 can bedownloaded to the computing device from an external computer or externalstorage device via a network (for example, the Internet, a local areanetwork or other, wide area network or wireless network) and networkadapter or interface 616. From the network adapter or interface 616, theprograms are loaded into the computer-readable tangible storage device608. The network may comprise copper wires, optical fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers.

Computing device 110 can also include a display screen 620, a keyboardor keypad 622, and a computer mouse or touchpad 624. Device drivers 612interface to display screen 620 for imaging, to keyboard or keypad 622,to computer mouse or touchpad 624, and/or to display screen 620 forpressure sensing of alphanumeric character entry and user selections.The device drivers 612, R/W drive or interface 614 and network adapteror interface 616 can comprise hardware and software (stored incomputer-readable tangible storage device 608 and/or ROM 606).

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

Based on the foregoing, a computer system, method and program producthave been disclosed for a presentation control system. However, numerousmodifications and substitutions can be made without deviating from thescope of the present invention. Therefore, the present invention hasbeen disclosed by way of example and not limitation.

What is claimed is:
 1. A method for sampling transactions frommulti-level log file records, a log file contains operation records,each operation record is of a certain type, each operation record isassociated with a transaction, the method comprising: reading aplurality of operation records from the log file into a record store;sampling records of the plurality of operation records of each operationrecord type at a predefined sampling rate; identifying operation recordsin the plurality of operations records associated with completedtransactions of which the sampled operation records are associated; andextracting the identified operation records from the record store into adata store.
 2. A method in accordance with claim 1, one operation recordassociated with a transaction is an end-of-transaction record indicatinga completed transaction, the method further comprising: reading one ofthe plurality of operation records from the log file into a recordstore; recording in a transaction-to-record table an association of theoperation record and the transaction to which the operation recordbelongs; in response to determining that the operation record is asampled record and the operation record is an end-of-transaction record,extracting all operation records from the record store into the datastore that are associated with the transaction based on thecorresponding association in the transaction-to-record table; inresponse to determining that the operation record is a sampled recordand the operation record is not an end-of-transaction record, recordingin an extraction-pending table the transaction to which the operationrecord belongs; and in response to determining that the operation recordis not a sampled record and the operation record is anend-of-transaction record and the transaction to which the operationrecord belongs is recorded in the extraction-pending table, extractingall operation records from the record store into the data store that areassociated with the transaction based on the corresponding associationin the transaction-to-record table.
 3. A method in accordance with claim1, wherein the plurality of operation records read from the log filefurther comprises a predefined number of operation records before andafter a sample set of operations records and the sampled records areselected from the sample set, such that substantially all operationrecords associated with the transactions with which the sampledoperation records are associated are in the plurality of operationrecords.
 4. A method in accordance with claim 1, one operation recordassociated with a transaction is an end-of-transaction record indicatinga completed transaction, further comprising: in response to determiningthat one of the plurality of operation records associated with atransaction with which a sampled operation record is associated is anend-of-transaction record, extracting the identified read operationrecords associated with the transaction to a data store.
 5. A method inaccordance with claim 1, wherein sampling records of the plurality ofoperation records further comprises randomly sampling a predeterminednumber of operation records of each operation record type in theplurality of operation records.
 6. A method in accordance with claim 1,wherein sampling records of the plurality of operation records furthercomprises sampling operation records of each operation record type at apredefined sampling rate associated with the operation record type.